Effect of Pressure-Propagation Behavior on Production Performance: Implication for Advancing Low-Permeability Coalbed-Methane Recovery

Abstract

Summary Low-permeability coalbed-methane (CBM) reservoirs possess unique pressure-propagation behavior, which can be classified further as the expansion characteristics of the drainage area and the desorption area [i.e., a formation in which the pressure is lower than the initial formation pressure and critical-desorption pressure (CDP), respectively]. Inevitably, several fluid-flow mechanisms will coexist in realistic coal seams at a certain production time, which is closely related to dynamic pressure and saturation distribution. To the best of our knowledge, a production-prediction model for CBM wells considering pressure-propagation behavior is still lacking. The objective of this work is to perform extensive investigations into the effect of pressure-propagation behavior on the gas-production performance of CBM wells. First, the pressure-squared approach is used to describe the pressure profile in the desorption area, which has been clarified as an effective-approximation method. Also, the pressure/saturation relationship that was developed in our previous research is used; therefore, saturation distribution can be obtained. Second, an efficient iteration algorithm is established to predict gas-production performance by combining a new gas-phase-productivity equation and a material-balance equation. Finally, using the proposed prediction model, we shed light on the optimization method for production strategy regarding the entire production life of CBM wells. Results show that the decrease rate of bottomhole pressure (BHP) should be slow at the water single-phase-flow stage, fast at the early gas/water two-phase-flow stage, and slow at the late gas/water two-phase-flow stage, which is referred to as the slow/fast/slow (SFS) control method. Remarkably, in the SFS control method, the decrease rate of the BHP at each period can be quantified on the basis of the proposed prediction model. To examine the applicability of the proposed SFS method, it is applied to an actual CBM well in Hancheng Field, China, and it enhances the cumulative gas production by a factor of approximately 1.65.